Overview

Dataset statistics

Number of variables12
Number of observations2773
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory281.6 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with unique_basket_sizeHigh correlation
basket_size is highly overall correlated with revenue and 1 other fieldsHigh correlation
distinct_stock_code is highly overall correlated with revenue and 3 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
revenue is highly overall correlated with basket_size and 3 other fieldsHigh correlation
total_products is highly overall correlated with basket_size and 3 other fieldsHigh correlation
total_purchases is highly overall correlated with distinct_stock_code and 2 other fieldsHigh correlation
unique_basket_size is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
avg_ticket is highly skewed (γ1 = 27.67827335)Skewed
frequency is highly skewed (γ1 = 46.07740946)Skewed
returned is highly skewed (γ1 = 21.6260127)Skewed
customer_id has unique valuesUnique
recency has 33 (1.2%) zerosZeros
returned has 1481 (53.4%) zerosZeros

Reproduction

Analysis started2024-05-24 23:40:32.738762
Analysis finished2024-05-24 23:41:16.846382
Duration44.11 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

UNIQUE 

Distinct2773
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15285.281
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:17.011861image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12626.6
Q113815
median15241
Q316780
95-th percentile17950.4
Maximum18287
Range5940
Interquartile range (IQR)2965

Descriptive statistics

Standard deviation1715.1526
Coefficient of variation (CV)0.11220942
Kurtosis-1.2070293
Mean15285.281
Median Absolute Deviation (MAD)1484
Skewness0.016612507
Sum42386085
Variance2941748.4
MonotonicityNot monotonic
2024-05-24T23:41:17.292763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17850 1
 
< 0.1%
14482 1
 
< 0.1%
17058 1
 
< 0.1%
17704 1
 
< 0.1%
16933 1
 
< 0.1%
13772 1
 
< 0.1%
16249 1
 
< 0.1%
14198 1
 
< 0.1%
13989 1
 
< 0.1%
17930 1
 
< 0.1%
Other values (2763) 2763
99.6%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18265 1
< 0.1%
18263 1
< 0.1%
18261 1
< 0.1%
18260 1
< 0.1%

revenue
Real number (ℝ)

HIGH CORRELATION 

Distinct2759
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2844.942
Minimum36.56
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:17.583387image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum36.56
5-th percentile264.548
Q1628
median1169.94
Q32423.32
95-th percentile7490.982
Maximum279138.02
Range279101.46
Interquartile range (IQR)1795.32

Descriptive statistics

Standard deviation10466.686
Coefficient of variation (CV)3.6790506
Kurtosis372.80205
Mean2844.942
Median Absolute Deviation (MAD)689.02
Skewness17.097705
Sum7889024.2
Variance1.0955151 × 108
MonotonicityNot monotonic
2024-05-24T23:41:17.883984image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1025.44 2
 
0.1%
745.06 2
 
0.1%
889.93 2
 
0.1%
734.94 2
 
0.1%
331 2
 
0.1%
1314.45 2
 
0.1%
379.65 2
 
0.1%
1353.74 2
 
0.1%
598.2 2
 
0.1%
1078.96 2
 
0.1%
Other values (2749) 2753
99.3%
ValueCountFrequency (%)
36.56 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
70.02 1
< 0.1%
77.4 1
< 0.1%
84.65 1
< 0.1%
90.3 1
< 0.1%
93.35 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
140438.72 1
< 0.1%
124564.53 1
< 0.1%
117375.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%
65019.62 1
< 0.1%

recency
Real number (ℝ)

ZEROS 

Distinct252
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.648395
Minimum0
Maximum372
Zeros33
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:18.168236image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q110
median29
Q373
95-th percentile211
Maximum372
Range372
Interquartile range (IQR)63

Descriptive statistics

Standard deviation68.422907
Coefficient of variation (CV)1.2078525
Kurtosis3.4305436
Mean56.648395
Median Absolute Deviation (MAD)23
Skewness1.8980349
Sum157086
Variance4681.6942
MonotonicityNot monotonic
2024-05-24T23:41:18.451399image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.6%
4 87
 
3.1%
2 85
 
3.1%
3 85
 
3.1%
8 76
 
2.7%
10 67
 
2.4%
9 66
 
2.4%
7 65
 
2.3%
17 62
 
2.2%
22 55
 
2.0%
Other values (242) 2026
73.1%
ValueCountFrequency (%)
0 33
 
1.2%
1 99
3.6%
2 85
3.1%
3 85
3.1%
4 87
3.1%
5 43
1.6%
7 65
2.3%
8 76
2.7%
9 66
2.4%
10 67
2.4%
ValueCountFrequency (%)
372 1
 
< 0.1%
366 1
 
< 0.1%
360 1
 
< 0.1%
358 3
0.1%
354 1
 
< 0.1%
337 1
 
< 0.1%
336 2
0.1%
334 1
 
< 0.1%
333 2
0.1%
330 1
 
< 0.1%

avg_recency_days
Real number (ℝ)

HIGH CORRELATION 

Distinct1155
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.756379
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:18.759083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13
Q134.222222
median59
Q399
95-th percentile224
Maximum366
Range365
Interquartile range (IQR)64.777778

Descriptive statistics

Standard deviation66.483798
Coefficient of variation (CV)0.84417032
Kurtosis3.6897278
Mean78.756379
Median Absolute Deviation (MAD)30
Skewness1.8311845
Sum218391.44
Variance4420.0954
MonotonicityNot monotonic
2024-05-24T23:41:19.084947image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70 21
 
0.8%
46 18
 
0.6%
55 17
 
0.6%
49 16
 
0.6%
31 16
 
0.6%
91 16
 
0.6%
21 15
 
0.5%
35 15
 
0.5%
42 15
 
0.5%
28 14
 
0.5%
Other values (1145) 2610
94.1%
ValueCountFrequency (%)
1 9
0.3%
2 4
0.1%
2.861538462 1
 
< 0.1%
3 6
0.2%
3.330357143 1
 
< 0.1%
3.351351351 1
 
< 0.1%
4 5
0.2%
4.191011236 1
 
< 0.1%
4.275862069 1
 
< 0.1%
4.5 1
 
< 0.1%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
364 1
 
< 0.1%
363 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

total_products
Real number (ℝ)

HIGH CORRELATION 

Distinct1631
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1669.2236
Minimum2
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:19.386023image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile119
Q1330
median699
Q31478
95-th percentile4614
Maximum196844
Range196842
Interquartile range (IQR)1148

Descriptive statistics

Standard deviation5885.8021
Coefficient of variation (CV)3.5260717
Kurtosis486.75708
Mean1669.2236
Median Absolute Deviation (MAD)449
Skewness18.198824
Sum4628757
Variance34642666
MonotonicityNot monotonic
2024-05-24T23:41:19.677521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
150 8
 
0.3%
246 8
 
0.3%
516 7
 
0.3%
1200 7
 
0.3%
200 7
 
0.3%
272 7
 
0.3%
219 7
 
0.3%
260 7
 
0.3%
300 7
 
0.3%
Other values (1621) 2697
97.3%
ValueCountFrequency (%)
2 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
25 1
< 0.1%
27 2
0.1%
30 1
< 0.1%
32 1
< 0.1%
33 2
0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
79963 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
62812 1
< 0.1%
58243 1
< 0.1%
57785 1
< 0.1%
50255 1
< 0.1%

distinct_stock_code
Real number (ℝ)

HIGH CORRELATION 

Distinct341
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.315543
Minimum1
Maximum1785
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:20.019313image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q129
median57
Q3105
95-th percentile239.4
Maximum1785
Range1784
Interquartile range (IQR)76

Descriptive statistics

Standard deviation98.71334
Coefficient of variation (CV)1.184813
Kurtosis80.51239
Mean83.315543
Median Absolute Deviation (MAD)33
Skewness6.3469448
Sum231034
Variance9744.3236
MonotonicityNot monotonic
2024-05-24T23:41:20.302654image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37 38
 
1.4%
24 37
 
1.3%
33 36
 
1.3%
26 36
 
1.3%
25 34
 
1.2%
18 33
 
1.2%
28 33
 
1.2%
30 32
 
1.2%
27 30
 
1.1%
23 29
 
1.0%
Other values (331) 2435
87.8%
ValueCountFrequency (%)
1 19
0.7%
2 13
0.5%
3 17
0.6%
4 18
0.6%
5 23
0.8%
6 19
0.7%
7 21
0.8%
8 24
0.9%
9 24
0.9%
10 19
0.7%
ValueCountFrequency (%)
1785 1
< 0.1%
1765 1
< 0.1%
1321 1
< 0.1%
1118 1
< 0.1%
883 1
< 0.1%
817 1
< 0.1%
717 1
< 0.1%
713 1
< 0.1%
699 1
< 0.1%
636 1
< 0.1%

total_purchases
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0544537
Minimum2
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:20.596788image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median4
Q36
95-th percentile17
Maximum206
Range204
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.0729125
Coefficient of variation (CV)1.4985518
Kurtosis183.89793
Mean6.0544537
Median Absolute Deviation (MAD)2
Skewness10.623447
Sum16789
Variance82.317741
MonotonicityNot monotonic
2024-05-24T23:41:20.885440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 780
28.1%
3 498
18.0%
4 393
14.2%
5 237
 
8.5%
6 173
 
6.2%
7 138
 
5.0%
8 98
 
3.5%
9 69
 
2.5%
10 55
 
2.0%
11 54
 
1.9%
Other values (45) 278
 
10.0%
ValueCountFrequency (%)
2 780
28.1%
3 498
18.0%
4 393
14.2%
5 237
 
8.5%
6 173
 
6.2%
7 138
 
5.0%
8 98
 
3.5%
9 69
 
2.5%
10 55
 
2.0%
11 54
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

basket_size
Real number (ℝ)

HIGH CORRELATION 

Distinct1931
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean230.94908
Minimum1
Maximum6009.3333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:21.192309image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45
Q1103.33333
median172
Q3278.09524
95-th percentile583.6
Maximum6009.3333
Range6008.3333
Interquartile range (IQR)174.7619

Descriptive statistics

Standard deviation261.5335
Coefficient of variation (CV)1.1324293
Kurtosis115.89887
Mean230.94908
Median Absolute Deviation (MAD)81
Skewness7.7349287
Sum640421.79
Variance68399.773
MonotonicityNot monotonic
2024-05-24T23:41:21.467424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
86 9
 
0.3%
60 8
 
0.3%
75 8
 
0.3%
197 7
 
0.3%
73 7
 
0.3%
82 7
 
0.3%
136 7
 
0.3%
105 7
 
0.3%
208 7
 
0.3%
Other values (1921) 2695
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
11.875 1
< 0.1%
ValueCountFrequency (%)
6009.333333 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%
2082.225806 1
< 0.1%
2000 1
< 0.1%
1903.5 1
< 0.1%
1866.933333 1
< 0.1%

unique_basket_size
Real number (ℝ)

HIGH CORRELATION 

Distinct1003
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.129792
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:21.747452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q110.133333
median17.307692
Q328.111111
95-th percentile56.648485
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.977778

Descriptive statistics

Standard deviation18.867714
Coefficient of variation (CV)0.85259337
Kurtosis24.175983
Mean22.129792
Median Absolute Deviation (MAD)8.3076923
Skewness3.1580319
Sum61365.914
Variance355.99064
MonotonicityNot monotonic
2024-05-24T23:41:22.047975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 44
 
1.6%
14 31
 
1.1%
11 29
 
1.0%
9 26
 
0.9%
1 26
 
0.9%
17.5 25
 
0.9%
10.5 25
 
0.9%
7.5 25
 
0.9%
9.5 24
 
0.9%
18 24
 
0.9%
Other values (993) 2494
89.9%
ValueCountFrequency (%)
1 26
0.9%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 7
 
0.3%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 21
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
203.5 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%
114 1
< 0.1%
110.3333333 1
< 0.1%
109.6666667 2
0.1%

avg_ticket
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2771
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.106572
Minimum2.1505882
Maximum4453.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:22.343972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.1505882
5-th percentile4.8524538
Q112.41668
median17.943444
Q325.025556
95-th percentile87.757474
Maximum4453.43
Range4451.2794
Interquartile range (IQR)12.608876

Descriptive statistics

Standard deviation107.63141
Coefficient of variation (CV)3.3523171
Kurtosis1054.6276
Mean32.106572
Median Absolute Deviation (MAD)6.3346556
Skewness27.678273
Sum89031.523
Variance11584.52
MonotonicityNot monotonic
2024-05-24T23:41:22.612876image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.47833333 2
 
0.1%
4.162 2
 
0.1%
25.6761194 1
 
< 0.1%
44.95564103 1
 
< 0.1%
32.59775 1
 
< 0.1%
19.03048387 1
 
< 0.1%
28.55451613 1
 
< 0.1%
12.80068182 1
 
< 0.1%
6.396214689 1
 
< 0.1%
26.08797101 1
 
< 0.1%
Other values (2761) 2761
99.6%
ValueCountFrequency (%)
2.150588235 1
< 0.1%
2.4325 1
< 0.1%
2.462371134 1
< 0.1%
2.511241379 1
< 0.1%
2.515333333 1
< 0.1%
2.65 1
< 0.1%
2.656931818 1
< 0.1%
2.707598253 1
< 0.1%
2.760621572 1
< 0.1%
2.770464191 1
< 0.1%
ValueCountFrequency (%)
4453.43 1
< 0.1%
1687.2 1
< 0.1%
952.9875 1
< 0.1%
872.13 1
< 0.1%
841.0214493 1
< 0.1%
651.1683333 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%
615.75 1
< 0.1%
602.4531323 1
< 0.1%

frequency
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1225
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.049706611
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:22.880300image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0087463557
Q10.015789474
median0.024390244
Q30.041666667
95-th percentile0.11538462
Maximum17
Range16.99455
Interquartile range (IQR)0.025877193

Descriptive statistics

Standard deviation0.33765504
Coefficient of variation (CV)6.7929604
Kurtosis2295.7098
Mean0.049706611
Median Absolute Deviation (MAD)0.010691614
Skewness46.077409
Sum137.83643
Variance0.11401092
MonotonicityNot monotonic
2024-05-24T23:41:23.188567image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0625 17
 
0.6%
0.02777777778 17
 
0.6%
0.02380952381 16
 
0.6%
0.08333333333 15
 
0.5%
0.09090909091 15
 
0.5%
0.03448275862 14
 
0.5%
0.02941176471 14
 
0.5%
0.07692307692 13
 
0.5%
0.02127659574 13
 
0.5%
0.02564102564 13
 
0.5%
Other values (1215) 2626
94.7%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%
1.142857143 1
 
< 0.1%
1 8
0.3%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%
0.5 3
 
0.1%

returned
Real number (ℝ)

SKEWED  ZEROS 

Distinct204
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.973675
Minimum0
Maximum9014
Zeros1481
Zeros (%)53.4%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-24T23:41:23.479924image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39
95-th percentile96.8
Maximum9014
Range9014
Interquartile range (IQR)9

Descriptive statistics

Standard deviation290.71429
Coefficient of variation (CV)8.3123747
Kurtosis571.74568
Mean34.973675
Median Absolute Deviation (MAD)0
Skewness21.626013
Sum96982
Variance84514.798
MonotonicityNot monotonic
2024-05-24T23:41:23.746755image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
53.4%
1 129
 
4.7%
2 117
 
4.2%
3 82
 
3.0%
4 72
 
2.6%
6 63
 
2.3%
5 55
 
2.0%
12 45
 
1.6%
8 39
 
1.4%
9 38
 
1.4%
Other values (194) 652
23.5%
ValueCountFrequency (%)
0 1481
53.4%
1 129
 
4.7%
2 117
 
4.2%
3 82
 
3.0%
4 72
 
2.6%
5 55
 
2.0%
6 63
 
2.3%
7 38
 
1.4%
8 39
 
1.4%
9 38
 
1.4%
ValueCountFrequency (%)
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%
1594 1
< 0.1%

Interactions

2024-05-24T23:41:11.661649image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:33.155642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:36.204835image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:39.335981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:42.549277image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:47.038790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:50.756941image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:53.938768image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:57.398623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:01.849911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:04.904130image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:07.929608image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:12.027527image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:33.398322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:36.462508image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:39.585471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:42.941647image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:47.304389image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:51.020497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:54.193897image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:57.748482image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:02.098904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:05.134350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:08.767048image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:12.428607image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:33.628146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:36.706973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:39.846449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:43.331102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:47.574129image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:51.264381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:54.445197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:58.100846image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:02.344230image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:05.403806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:09.029927image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:12.768916image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:33.883786image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:36.963370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:40.104511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:43.686603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:47.836825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:51.532240image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:54.701059image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:58.416670image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:02.594962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:05.653961image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:09.301692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:13.146093image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:34.155014image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:37.239883image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:40.377017image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:44.035844image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:48.096761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:51.798407image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:54.980914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:58.831431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:02.852889image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:05.921350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:09.571696image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:13.527343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:34.423137image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:37.512354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:40.655273image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:44.494991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:48.887801image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:52.072256image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:55.261110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:59.272084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:03.123206image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:06.190771image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:09.845452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:13.863740image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:34.671559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:37.772657image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:40.913767image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:44.879447image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:49.153970image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:52.331316image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:55.527576image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:59.642153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:03.389938image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:06.453120image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:10.104333image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:14.236032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:34.936262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:38.041752image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:41.188089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:45.302363image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:49.421591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:52.620332image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:55.805793image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:00.080050image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:03.650105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:06.713239image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:10.367316image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:14.644831image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:35.198953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:38.309585image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:41.454610image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:45.696744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:49.707307image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:52.895321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:56.069491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:00.471349image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:03.898196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:06.965947image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:10.621347image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:15.011176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:35.455018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:38.568875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:41.715604image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:46.173524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:49.959113image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:53.153671image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:56.326997image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:00.881734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:04.156797image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:07.204916image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:10.884310image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:15.344141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:35.692352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:38.828864image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:41.952119image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:46.527847image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:50.208656image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:53.404485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:56.646018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:01.290200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:04.402284image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:07.445600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:11.110841image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:15.780098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:35.938928image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:39.084938image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:42.241373image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:46.796628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:50.476801image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:53.676976image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:40:57.042927image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:01.601243image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:04.665982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:07.698758image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-24T23:41:11.366919image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-05-24T23:41:23.984529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
avg_recency_daysavg_ticketbasket_sizecustomer_iddistinct_stock_codefrequencyrecencyreturnedrevenuetotal_productstotal_purchasesunique_basket_size
avg_recency_days1.000-0.080-0.043-0.012-0.221-0.9520.225-0.215-0.367-0.344-0.4760.062
avg_ticket-0.0801.0000.198-0.141-0.4650.0820.0350.1880.2730.1950.091-0.626
basket_size-0.0430.1981.000-0.1210.4000.026-0.1030.2140.6020.7590.1260.433
customer_id-0.012-0.141-0.1211.0000.0090.0140.014-0.058-0.086-0.0790.0130.006
distinct_stock_code-0.221-0.4650.4000.0091.0000.141-0.3360.2820.6350.6330.5440.798
frequency-0.9520.0820.0260.0140.1411.000-0.1270.1760.2590.2400.322-0.071
recency0.2250.035-0.1030.014-0.336-0.1271.000-0.186-0.373-0.365-0.448-0.105
returned-0.2150.1880.214-0.0580.2820.176-0.1861.0000.4610.4260.4270.027
revenue-0.3670.2730.602-0.0860.6350.259-0.3730.4611.0000.9220.7630.282
total_products-0.3440.1950.759-0.0790.6330.240-0.3650.4260.9221.0000.7040.312
total_purchases-0.4760.0910.1260.0130.5440.322-0.4480.4270.7630.7041.0000.016
unique_basket_size0.062-0.6260.4330.0060.798-0.071-0.1050.0270.2820.3120.0161.000

Missing values

2024-05-24T23:41:16.183220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-24T23:41:16.632893image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idrevenuerecencyavg_recency_daystotal_productsdistinct_stock_codetotal_purchasesbasket_sizeunique_basket_sizeavg_ticketfrequencyreturned
0178505391.21372.01.0000001733.021.034.050.9705888.73529418.15222217.00000040.0
1130473232.5956.052.8333331390.0105.09.0154.44444419.00000018.9040350.02830235.0
2125836705.382.026.5000005028.0114.015.0335.20000015.46666728.9025000.04032350.0
313748948.2595.092.666667439.024.05.087.8000005.60000033.8660710.0179210.0
415100876.00333.020.00000080.01.03.026.6666671.000000292.0000000.07317122.0
5152914623.3025.026.7692312102.061.014.0150.1428577.28571445.3264710.04011529.0
6146885630.877.019.2631583621.0148.021.0172.42857115.57142917.2197860.057221399.0
7178095411.9116.039.6666672057.046.012.0171.4166675.08333388.7198360.03352041.0
81531160767.900.04.19101138194.0567.091.0419.71428626.14285725.5434640.243316474.0
9160982005.6387.047.666667613.034.07.087.5714299.57142929.9347760.0243900.0
customer_idrevenuerecencyavg_recency_daystotal_productsdistinct_stock_codetotal_purchasesbasket_sizeunique_basket_sizeavg_ticketfrequencyreturned
561017290525.243.013.0404.092.02.0202.00000051.05.1494120.1428570.0
56191478577.4010.05.084.02.02.042.0000001.525.8000000.3333330.0
562017254272.444.011.0252.0100.02.0126.00000056.02.4325000.1666670.0
563617232421.522.012.0203.030.02.0101.50000018.011.7088890.1538460.0
563717468137.0010.04.0116.05.02.058.0000002.527.4000000.4000000.0
564813596697.045.07.0406.0133.02.0203.00000083.04.1990360.2500000.0
5654148931237.859.02.0799.072.02.0399.50000036.516.9568490.6666670.0
567914126706.137.03.0508.014.03.0169.3333335.047.0753330.75000050.0
5685135211092.391.04.5733.0312.03.0244.333333145.02.5112410.3000000.0
569515060301.848.01.0262.080.04.065.50000030.02.5153332.0000000.0